GEOSPATIAL BIG DATA PROCESSING IN HYBRID CLOUD ENVIRONMENTS

被引:0
|
作者
Simonis, Ingo [1 ]
机构
[1] OGC, Kriftel, Germany
基金
欧盟地平线“2020”;
关键词
Geospatial; Big Data; Standards; Cloud;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The importance of big geospatial data hosted on cloud environments is constantly growing. Main reasons are the rapid increase in volume of remote sensing data, the trend to persistently store and share more in-situ data at higher sampling rates, and the reduced management overhead of data hosted on commercial cloud platforms compared to inhouse solutions. At the same time, cloud computing has the advantage of high scalability (and often reliability) and the capability to match the increasing computational requirements entailed by Big Data processing. This paper discusses interoperability and portability issues of cloud computing architectures and introduces a standards-based architecture to facilitate geospatial big data processing in hybrid cloud environments by leveraging and extending standards released by the Open Geospatial Consortium, OGC.
引用
收藏
页码:419 / 421
页数:3
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